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davidbirchall/squad-skills-ai-engineering

v0.2.0

AI engineering skills for LLM-powered applications and agent systems: LLM integration, prompt engineering, agent design and orchestration, tool and MCP integration, context engineering, retrieval-augmented generation, evaluation, testing, security, and observability.

tool-integration

Designing tools (function calling) that LLM agents invoke in a TypeScript/Node/NestJS backend - schema design, naming and descriptions, input validation, idempotency, error results the model can act on, permissions and authorisation, side-effect classification, confirmation for destructive tools, result size limits, parallel tool calls, and timeouts. Provider-agnostic. Load when defining, reviewing, or debugging tools an agent or chat model can call.

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